Produce artifacts for bare metal installation in Dockerfile.openvino

Fix logging lint errors

…factor

Dockerfile improvements: multistage

* Fix setup.py for HPU

* Fix  vllm._C import ops -> vllm.hpu import ops

* more of the same thing

* re-add hpex rmsnorm and rope; but rope is crashing

* remove unnecessary comments

* add vllm/hpu files

* add hpu autodetection

* Add HabanaAttention stub

* revert accidental changes

* revert non-habana backend attention changes

* add habana attention/worker/executor, sampling fails now

* Restore unnecessarily changed files

* enable HabanaMemoryProfiler

* Make sampler pass

* restore habana fused rope

* prefill is now working!!!

* fix prefill padding; decode is now working!!!!!

* revert accidental changes

* remove unused stuff in habana_paged_attn.py

* remove diagnostic stuff from llm_engine.py

* use HabanaExecutorAsync in async_llm_engine.py

* add habana copyright headers to habana_*.py files

* fix prefill attention conformance

* minor naming fixes

* remove naive attention from habana_attn (it never worked anyway)

* re-enable profile run

* Add fake HPUGraph support

* add more metrics

* indentation fix

* ~~recipe cache metrics don't work lalalala~~

* i'm done with metrics for now

* fix corner case in which hl-smi is not available but synapse is

* FIXME: temporary setup.py workaround

* WIP: add tensor parallelism stubs

* habana worker cleanup

* tensor parallelism is now working

* remove unused files

* remove unused func

* add hpugraphrunner

* improve hpu layernorm

* Port pipelined PA

* Port context length bucketing

* remove cudagraphrunner from hpu runner

* restore HPUGraphRunner back from FakeHPUGraphRunner

* handle rotary embeddings properly on gaudi3

* oopsie! captured_block_counts was incorrect!

* captured_block_counts.append doesn't do anything

* Restore habana_main KV cache memory layout

* fix memory profiler

* overhaul hpugraph capture

* memory profiling overhaul

* format memory properly in model warmup

* add graph compilation profiler for graph capture phase

* adroll back log lvl on graph capture message

* Remove unnecessary view on residual connection in RMSNorm (vllm-project#25)

---------

Co-authored-by: madamczykhabana <110973826+madamczykhabana@users.noreply.github.com>

Added Qwen MoE

…integration

[Feature] DeepGEMM integration

Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>

afd适配mtp和量化+bug fix

…t-processor

[Engine]Refactor output processing for multimodal capabilities in vLLM-omni

…llm-project#10, closes vllm-project#20)

Implements reallocate_lora_weights(new_slots) so stacked GPU tensors can
be resized at runtime without restarting the server.

- BaseLayerWithLoRA: single implementation with _reallocate() helper that
  handles both tuple-of-tensors (linear layers) and plain-tensor
  (LogitsProcessorWithLoRA) storage via isinstance check. All linear layer
  subclasses inherit this for free.
- FusedMoEWithLoRA: override to reallocate the four w13/w2 weight tuples,
  resize adapter_enabled, rebuild the flat lora_a/b_stacked views list,
  and update max_loras. FusedMoE3DWithLoRA inherits this override.
- 22 CPU-only unit tests in tests/lora/test_reallocate_lora_weights.py
  covering shape after grow/shrink, weight preservation for surviving slots,
  zero-init of new slots, no-op before create_lora_weights, and no
  empty_cache() call inside the method.

Pre-commit: ruff-check, ruff-format, mypy-3.10 all pass.
Tests: 22/22 pass on CPU.

AI assistance was used (Claude Code). All changed lines reviewed by
@yuezhu1. This does not duplicate any existing upstream PR or issue.

Co-authored-by: Claude <noreply@anthropic.com>